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# Autogenerated By   : src/main/python/generator/generator.py
# Autogenerated From : scripts/builtin/img_sample_pairing_linearized.dml

from typing import Dict, Iterable

from systemds.operator import OperationNode, Matrix, Frame, List, MultiReturn, Scalar
from systemds.utils.consts import VALID_INPUT_TYPES


def img_sample_pairing_linearized(img_in1: Matrix,
                                  img_in2: Matrix,
                                  weight: float):
    """
     The image sample pairing function blends two images together.
    
     .. code-block:: python
    
       >>> import numpy as np
       >>> from systemds.context import SystemDSContext
       >>> from systemds.operator.algorithm import img_sample_pairing_linearized
       >>> 
       >>> with SystemDSContext() as sds:
       ...     img_in1 = sds.from_numpy(
       ...         np.array([[ 10., 20., 30.,
       ...                     40., 50., 60.,
       ...                     70., 80., 90. ]], dtype=np.float32)
       ...     )
       ...     img_in2 = sds.from_numpy(
       ...         np.array([[ 30., 40., 50.,
       ...                     60., 70., 80.,
       ...                     90., 100., 110. ]], dtype=np.float32)
       ...     )
       ...     result_img = img_sample_pairing_linearized(img_in1, img_in2, 0.5).compute()
       ...     print(result_img.reshape(3, 3))
       [[ 20.  30.  40.]
        [ 50.  60.  70.]
        [ 80.  90. 100.]]
    
    
    
    
    :param img_in1: Input images as linearized 2D matrix with top left corner at [1, 1] (every row represents a linearized matrix/image)
    :param img_in2: Second input image (one image represented as a single row linearized matrix)
    :param weight: The weight given to the second image.
        0 means only img_in1, 1 means only img_in2 will be visible
    :return: Output image
    """

    params_dict = {'img_in1': img_in1, 'img_in2': img_in2, 'weight': weight}
    return Matrix(img_in1.sds_context,
        'img_sample_pairing_linearized',
        named_input_nodes=params_dict)
